The present invention relates generally to medical diagnostic imaging systems and, more particularly, to a technique for temporal analysis of images. The present technique utilizes image compression techniques and a remote applications server to perform image matching and subtraction remotely and independently from the client-side computing system.
Medical diagnostic and imaging systems are ubiquitous in modern health care facilities. Currently, a number of modalities exist for medical diagnostic and imaging systems. These include computed tomography (CT) systems, x-ray systems (including both conventional and digital or digitized imaging systems), magnetic resonance (MR) systems, positron emission tomography (PET) systems, ultrasound systems, nuclear medicine systems, and so forth. Such systems provide invaluable tools for identifying, diagnosing and treating physical conditions and greatly reduce the need for surgical diagnostic intervention. In many instances, these modalities complement one another and offer the physician a range of techniques for imaging particular types of tissue, organs, physiological systems, and so forth. Health care institutions often dispose of several such imaging systems at a single or multiple facilities, permitting its physicians to draw upon such resources as required by particular patient needs. In many instances, final diagnosis and treatment proceeds only after an attending physician or radiologist has complemented conventional examinations with detailed images of relevant areas and tissues via one or more imaging modalities.
It is often desirable to compare physiological images of a patient over a period of medical treatment to evaluate any physiological changes in the patient, the progress of a disease (e.g., cancer), or the effectiveness of a medical treatment. The present approach is to use image subtraction techniques to obtain an image highlighting the temporally changed areas in a series of medical images. For example, an image obtained six months ago may be subtracted from a current image to highlight (or reveal) a cancerous growth in a subject. Unfortunately, the images may be stored at many different health facilities in which the patient sought treatment and/or medical imaging. Moreover, each facility may have different operating systems, medical systems, image storage systems and so forth. These incompatibilities and the geographically scattered storage of medical images complicate the temporal analysis of medical diagnostic images, which are typically stored as very large files (e.g. 10 MB).
Accordingly, there is a need for a technique for temporal analysis of medical diagnostic images that is independent of the particular platform utilized at a medical facility. More particularly, a technique is needed for remotely processing medical diagnostic images and for integrating medical imaging and storage systems at a plurality of medical facilities.